peakFilter-methods {Cardinal}R Documentation

Peak filter or mass filter an imaging dataset

Description

Apply peak filtering or mass filtering to a mass spectrometry imaging dataset.

Usage

## S4 method for signature 'MSImagingExperiment'
mzFilter(object, ..., freq.min = 0, thresh.max = 0.01)

## S4 method for signature 'MSImagingExperiment'
peakFilter(object, ..., freq.min = 0.01, thresh.max = 0)

## S4 method for signature 'MSImageSet'
peakFilter(object, method = "freq", ..., pixel, plot)

## Filter based on the frequency of a peak
peakFilter.freq(x, freq.min=0.01, ...)

Arguments

object

An object of class MSImageSet.

freq.min

Minimum frequency; peaks that occur in the dataset in lesser proportion than this will be dropped.

thresh.max

Minimum threshold relative to maximum mean intensity; features with mean intensity lesser than this, as a proportion of the maximum intensity in the mean spectrum, will be dropped.

...

Additional arguments passed to the peak filtering method, or conditions evaluating to logical vectors where only those conditions that are TRUE are retained.

method

The peak filtering method to use.

pixel

Deprecated.

plot

Deprecated. (Never did anything anyway.)

x

The vector of ion image intensities to filter.

Details

When applied to a MSImagingExperiment object, peakFilter uses the summarize() to generate useful statistics about the detected peaks. These include the ‘min’, ‘max’, ‘mean’, ‘sum’, ‘sd’, and ‘var’ of the detected peaks. These can be used in logical expressions to filter the peaks.

Note that mzFilter is an alias for peakFilter, with different default parameters that are more appropriate for data that has not been peak picked and aligned.

When applied to a MSImageSet object, unlike most other processing methods, peakFilter operates on the feature space (ion images) of the dataset.

Peak filtering is usually performed using the provided functions, but a user-created function can also be passed to method. In this case it should take the following arguments:

A user-created function should return a logical: TRUE means keep the peak, and FALSE means remove the peak.

Internally, featureApply is used to apply the filtering. See its documentation page for more details on additional objects available to the environment installed to the peak filtering function.

Value

An object of the same class with the filtered peaks.

Author(s)

Kylie A. Bemis

See Also

MSImagingExperiment, MSImageSet, peakPick, peakAlign, peakBin, reduceDimension, featureApply, process

Examples

register(SerialParam())

set.seed(2)
data <- simulateImage(preset=1, npeaks=10, dim=c(3,3))
data <- data[,pData(data)$circle]

# queue peak picking, alignment, and filtering
data <- peakPick(data, method="simple", SNR=6)
data <- peakAlign(data, tolerance=200, units="ppm")
data <- peakFilter(data, freq.min=0.2)

# apply peak picking, alignment, and filtering
data_peaks <- process(data, plot=interactive())

[Package Cardinal version 2.2.6 Index]